Triple

T37834440
Position Surface form Disambiguated ID Type / Status
Subject Universidade de Caxias do Sul E943296 entity
Predicate hasCampus P116 FINISHED
Object Nova Petrópolis campus
Nova Petrópolis campus is a regional branch of the Universidade de Caxias do Sul that offers higher education programs and services to students in and around the city of Nova Petrópolis, Brazil.
E2253381 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Nova Petrópolis campus | Statement: [Universidade de Caxias do Sul, hasCampus, Nova Petrópolis campus]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nova Petrópolis campus
Triple: [Universidade de Caxias do Sul, hasCampus, Nova Petrópolis campus]
Generated description
Nova Petrópolis campus is a regional branch of the Universidade de Caxias do Sul that offers higher education programs and services to students in and around the city of Nova Petrópolis, Brazil.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f76eea4c8c8190a335aed5955cf2db completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbb1f19de0819096e678ea623597aa completed May 6, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41542296d88190a57fb0891cb899c5 completed June 28, 2026, 5:04 p.m.
NEDg Description generation batch_6a415595562c8190b47fec2243f0157c completed June 28, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_6a41560e36508190b2b36868187f316b completed June 28, 2026, 5:12 p.m.
Created at: May 3, 2026, 4:19 p.m.